The Library System of the United States

Data Visualization – Final Project

Important Resources and Links

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To see our GitHub repository, click here.

To see our Shiny application, click here.

Session Information

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sessionInfo(package=NULL)

R version 3.3.2 (2016-10-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C                           LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] plyr_1.8.4  readr_1.1.0

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.10    digest_0.6.11   rprojroot_1.2   R6_2.2.0        jsonlite_1.4    backports_1.0.5 magrittr_1.5   
 [8] evaluate_0.10   stringi_1.1.2   rmarkdown_1.3   tools_3.3.2     stringr_1.1.0   hms_0.3         yaml_2.1.14    
[15] base64enc_0.1-3 htmltools_0.3.5 knitr_1.15.1    tibble_1.3.0   

The ETL Script

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source("states_ETLscript.R")

Parsed with column specification:
cols(
  .default = col_integer(),
  State = col_character(),
  `MLS Librarians` = col_double(),
  Librarians = col_double(),
  Employees = col_double(),
  `Total Staff` = col_double(),
  `Downloadable Audio` = col_double(),
  `Downloadable Video` = col_double(),
  `Start Date` = col_character(),
  `End Date` = col_character()
)
See spec(...) for full column specifications.

Classes ‘tbl_df’, ‘tbl’ and 'data.frame':   51 obs. of  62 variables:
 $ Submission Year                      : int  2015 2015 2015 2015 2015 2015 2015 2015 2015 2015 ...
 $ State                                : chr  "AK" "AL" "AR" "AZ" ...
 $ State Code                           : int  2 1 5 4 6 8 9 11 10 12 ...
 $ Region Code                          : int  8 5 5 6 8 7 1 2 2 5 ...
 $ Service Population                   : int  652274 4822023 2833849 10501253 38322887 5238320 4374214 658893 925244 19813366 ...
 $ Service Population Without Duplicates: int  652274 4822023 2643928 6667241 38322887 5177510 3596080 658893 925244 19464451 ...
 $ State Population                     : int  735601 4822023 2915918 6667241 38340074 5264890 3596080 658893 925244 19839251 ...
 $ Central Libraries                    : int  85 221 54 85 167 97 192 1 19 63 ...
 $ Branch Libraries                     : int  16 76 179 135 950 162 47 25 13 468 ...
 $ Bookmobiles                          : int  1 14 2 11 53 13 4 0 2 24 ...
 $ MLS Librarians                       : num  58.8 329.6 142 461.3 2976.5 ...
 $ Librarians                           : num  113 736 286 546 3210 ...
 $ Employees                            : num  191 1081 767 1485 8388 ...
 $ Total Staff                          : num  303 1817 1053 2032 11598 ...
 $ Local Government Operating Revenue   : int  32474960 88056291 64665467 157746903 1265099905 265575219 168823962 53095222 19805621 461436699 ...
 $ State Government Operating Revenue   : int  1176158 4736727 5495428 1611605 13614724 1233937 1618933 0 3997939 22913457 ...
 $ Federal Government Operating Revenue : int  1166883 1081174 0 2029032 4633053 772338 330504 912671 2053 1181115 ...
 $ Other Operating Revenue              : int  3122020 9247116 4633340 7024609 71630786 16374433 24624113 180898 1861803 20302059 ...
 $ Total Operating Revenue              : int  37940021 103121308 74794235 168412149 1354978468 283955927 195397512 54188791 25667416 505833330 ...
 $ Salaries                             : int  13969263 54292921 33653433 77164201 565090291 129272590 114615887 31828080 12628074 225861289 ...
 $ Benefits                             : int  9212580 14390910 10389231 28609129 281367947 36756147 33333225 6851322 4724159 81550783 ...
 $ Total Staff Expenditures             : int  23181843 68683831 44042664 105773330 846458238 166028737 147949112 38679402 17352233 307412072 ...
 $ Print Collection Expenditures        : int  2276916 6505277 5533401 14556902 68898041 16445553 12363802 2000732 1797136 33012867 ...
 $ Digital Collection Expenditures      : int  488715 1413812 2023580 6231405 24944727 9371697 3577446 1340000 158409 16421139 ...
 $ Other Collection Expenditures        : int  569660 2701279 1895616 5788517 18886309 9594308 3217904 495000 635597 10771442 ...
 $ Total Collection Expenditures        : int  3335291 10620368 9452597 26576824 112729077 35411558 19159152 3835732 2591142 60205448 ...
 $ Other Operating Expenditures         : int  9991895 20658148 18375101 44262826 326843919 61043834 36150456 11798205 5049298 143395285 ...
 $ Total Operating Expenditures         : int  36509029 99962347 71870362 176612980 1286031234 262484129 203258720 54313339 24992673 511012805 ...
 $ Local Government Capital Revenue     : int  4206200 1835628 6288532 7588520 50568512 10236392 9834713 12950000 148240 23899274 ...
 $ State Government Capital Revenue     : int  20786393 0 289274 30000 203848 42120 3037860 0 3142715 558107 ...
 $ Federal Government Capital Revenue   : int  500000 191962 0 55484 74604 0 216618 0 0 0 ...
 $ Other Capital Revenue                : int  1289455 1435752 611755 83500 11337389 3663220 9350986 0 1723942 378930 ...
 $ Total Capital Revenue                : int  26782048 3463342 7189561 7757504 62184353 13941732 22440177 12950000 5014897 24836311 ...
 $ Total Capital Expenditures           : int  18337915 4777481 8489855 3436844 82960891 45987892 26583582 10353699 10029794 27841697 ...
 $ Print Collection                     : int  2434236 9442086 6304377 8229850 65409430 10316703 14577630 1815540 1642715 31602986 ...
 $ Digital Collection                   : int  351606 2714815 532433 1367378 2978360 1390637 1312468 177086 415170 1797802 ...
 $ Audio Collection                     : int  116847 450144 230003 689616 3530931 922877 826586 86416 114600 1947487 ...
 $ Downloadable Audio                   : num  373121 646206 185583 694223 564568 ...
 $ Physical Video                       : int  277268 620827 401308 1116663 5139201 1344808 1122198 140667 175643 3520618 ...
 $ Downloadable Video                   : num  1181 27411 10028 6281 135125 ...
 $ Local Cooperative Agreements         : int  695 974 563 969 3947 2160 1687 74 54 1844 ...
 $ State Licensed Databases             : int  4116 12737 3016 2430 116 0 7606 0 651 4838 ...
 $ Total Licensed Databases             : int  4811 13711 3579 3399 4063 2160 9293 74 705 6682 ...
 $ Print Subscriptions                  : int  5600 8932 10137 14239 92902 25553 21268 2071 4354 43118 ...
 $ Hours Open                           : int  153410 626821 445052 482261 2267921 608043 551274 65208 85420 1244917 ...
 $ Library Visits                       : int  3491307 17217402 10973629 27609711 164300175 32981666 21972583 4230790 3834672 75553933 ...
 $ Reference Transactions               : int  392428 4417062 2282111 5754966 23208453 4208956 3494403 921814 405585 23686241 ...
 $ Registered Users                     : int  358089 2663716 1615238 3118825 21723648 3588616 1647190 359371 379791 10615421 ...
 $ Circulation Transactions             : int  4792662 20526321 14390348 43672067 222788583 64683932 31081616 3938767 6180769 116693486 ...
 $ Interlibrary Loans Provided          : int  27745 427590 28247 324668 3567561 786027 934646 0 842407 98964 ...
 $ Interlibrary Loans Received          : int  28177 412054 26991 367263 3512390 879725 918765 180 816950 125338 ...
 $ Library Programs                     : int  12803 42145 34227 73875 342664 106717 95517 14357 13056 203578 ...
 $ Childrens Programs                   : int  8802 21685 21081 37852 206627 67253 54737 8514 5408 96748 ...
 $ Young Adult Programs                 : int  1528 4844 4620 6702 33645 9064 7381 1566 1197 17006 ...
 $ Library Program Audience             : int  279080 1053347 997901 1472963 9491467 2647097 2003864 284969 256274 4611959 ...
 $ Childrens Program Audience           : int  202322 696970 712783 1034731 6909344 1799469 1226174 225815 175335 2928059 ...
 $ Young Adult Program Audience         : int  25902 77371 88721 109545 531379 151930 112501 15624 17349 314348 ...
 $ Public Internet Computers            : int  998 5302 2596 5593 21735 6407 4355 1000 772 16781 ...
 $ Internet Computer Use                : int  772129 4359414 1970448 8255038 35000501 7395748 4465464 1050623 622515 19076151 ...
 $ Wireless Internet Sessions           : int  479245 15224387 160450 5880952 14252610 6234884 524318 -1 139907 3276803 ...
 $ Start Date                           : chr  "Jan-13" "Oct-13" "Jan-14" "Jul-13" ...
 $ End Date                             : chr  "Jun-14" "Sep-14" "Dec-14" "Jun-14" ...
 - attr(*, "spec")=List of 2
  ..$ cols   :List of 62
  .. ..$ Submission Year                      : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ State                                : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ State Code                           : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Region Code                          : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Service Population                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Service Population Without Duplicates: list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ State Population                     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Central Libraries                    : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Branch Libraries                     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Bookmobiles                          : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ MLS Librarians                       : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Librarians                           : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Employees                            : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Total Staff                          : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Local Government Operating Revenue   : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ State Government Operating Revenue   : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Federal Government Operating Revenue : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Other Operating Revenue              : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Operating Revenue              : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Salaries                             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Benefits                             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Staff Expenditures             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Print Collection Expenditures        : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Digital Collection Expenditures      : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Other Collection Expenditures        : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Collection Expenditures        : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Other Operating Expenditures         : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Operating Expenditures         : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Local Government Capital Revenue     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ State Government Capital Revenue     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Federal Government Capital Revenue   : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Other Capital Revenue                : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Capital Revenue                : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Capital Expenditures           : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Print Collection                     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Digital Collection                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Audio Collection                     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Downloadable Audio                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Physical Video                       : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Downloadable Video                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_double" "collector"
  .. ..$ Local Cooperative Agreements         : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ State Licensed Databases             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Total Licensed Databases             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Print Subscriptions                  : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Hours Open                           : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Library Visits                       : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Reference Transactions               : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Registered Users                     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Circulation Transactions             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Interlibrary Loans Provided          : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Interlibrary Loans Received          : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Library Programs                     : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Childrens Programs                   : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Young Adult Programs                 : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Library Program Audience             : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Childrens Program Audience           : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Young Adult Program Audience         : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Public Internet Computers            : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Internet Computer Use                : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Wireless Internet Sessions           : list()
  .. .. ..- attr(*, "class")= chr  "collector_integer" "collector"
  .. ..$ Start Date                           : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  .. ..$ End Date                             : list()
  .. .. ..- attr(*, "class")= chr  "collector_character" "collector"
  ..$ default: list()
  .. ..- attr(*, "class")= chr  "collector_guess" "collector"
  ..- attr(*, "class")= chr "col_spec"
CREATE TABLE 00_Docstates State varchar2(4000),
 Service Population Without Duplicates varchar2(4000),
 MLS Librarians varchar2(4000),
 Childrens Programs varchar2(4000),
 Childrens Program Audience varchar2(4000),
 Start Date varchar2(4000),
 End Date varchar2(4000),
 Submission Year number(38,4),
 State Code number(38,4),
 Region Code number(38,4),
 Service Population number(38,4),
 Service Population without Duplicates number(38,4),
 State Population number(38,4),
 Central Libraries number(38,4),
 Branch Libraries number(38,4),
 Bookmobiles number(38,4),
 MLS Libraries number(38,4),
 Librarians number(38,4),
 Employees number(38,4),
 Total Staff number(38,4),
 Local Government Operating Revenue number(38,4),
 State Government Operating Revenue number(38,4),
 Federal Government Operating Revenue number(38,4),
 Other Operating Revenue number(38,4),
 Total Operating Revenue number(38,4),
 Salaries number(38,4),
 Benefits number(38,4),
 Benefits number(38,4),
 Total Staff Expenditures number(38,4),
 Print Collection Expenditures number(38,4),
 Digital Collection Expenditures number(38,4),
 Other Collection Expenditures number(38,4),
 Total Collection Expenditures number(38,4),
 Other Operating Expenditures number(38,4),
 Total Operating Expenditures number(38,4),
 Local Government Capital Revenue number(38,4),
 State Government Capital Revenue number(38,4),
 Federal Government Capital Revenue number(38,4),
 Other Capital Revenue number(38,4),
 Total Capital Revenue number(38,4),
 Total Capital Expenditures number(38,4),
 Print Collection number(38,4),
 Digital Collection number(38,4),
 Audio Collection number(38,4),
 Downloadable Audio number(38,4),
 Physical Video number(38,4),
 Downloadable Video number(38,4),
 Local Cooperative Agreements number(38,4),
 State Licensed Databases number(38,4),
 Total Licensed Databases number(38,4),
 Print Subscriptions number(38,4),
 Hours Open number(38,4),
 Library Visits number(38,4),
 Reference Transactions number(38,4),
 Registered Users number(38,4),
 Circulation Transactions number(38,4),
 Interlibrary Loans Provided number(38,4),
 Interlibrary Loans Received number(38,4),
 Library Programs number(38,4),
 Children's Programs number(38,4),
 Young Adult Programs number(38,4),
 Library Program Audience number(38,4),
 Children's Program Audience number(38,4),
 Young Adult Program Audience number(38,4),
 Public Internet Computers number(38,4),
 Internet Computer Use number(38,4),
 Wireless Internet Sessions number(38,4)
 );

Summary of Library Data

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This data set is from kaggle. You can find this data here. It provides detailed information about libraries in each state in the United States.

summary(states)

   Length     Class      Mode 
        1 character character 

Summary of Subsets of Library Data

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This data is a subset of the library data that was re-configured to make Digital Cost, Other Cost, Print Cost, and Total Cost to be a subset of a larger category – Collection Cost Type. This way, the data could be easily grouped on the same visualization.

summary(states_boxplot)

    State             Category              Cost          
 Length:204         Length:204         Min.   :    76731  
 Class :character   Class :character   1st Qu.:  2429076  
 Mode  :character   Mode  :character   Median :  5843598  
                                       Mean   : 12503265  
                                       3rd Qu.: 15685597  
                                       Max.   :112729077  

This data is a subset of the library data that was re-configured to make Children’s Programs, Young Adult Programs, and Adult Programs to be a subset of a larger category – Program Type. This way, the data could be easily grouped on the same visualization.

summary(Program_Category)

    State           Program_Category    Num_Programs   
 Length:153         Length:153         Min.   :  1172  
 Class :character   Class :character   1st Qu.:  7381  
 Mode  :character   Mode  :character   Median : 22070  
                                       Mean   : 48917  
                                       3rd Qu.: 62120  
                                       Max.   :500005  

Summary of Census Data

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This data set is from the census data on data.world. You can find this data here. It provides the number of employed persons in each state.

summary(census_employment)

    State              Employed       
 Length:52          Min.   :  456640  
 Class :character   1st Qu.: 1398759  
 Mode  :character   Median : 3335384  
                    Mean   : 4886644  
                    3rd Qu.: 5501786  
                    Max.   :30312429  

This data set is from the census data on data.world. You can find this data here. It provides the number of people enrolled in high school in each state.

summary(census_enrollment)

    State           Enrollment_9to12 
 Length:52          Min.   :  24198  
 Class :character   1st Qu.:  91860  
 Mode  :character   Median : 215712  
                    Mean   : 331031  
                    3rd Qu.: 362992  
                    Max.   :2216175  

This data set is from the census data on data.world. You can find this data here. It provides the median family income in each state.

summary(Median_Family_Income)

    State             B19119_001   
 Length:52          Min.   :22976  
 Class :character   1st Qu.:57986  
 Mode  :character   Median :65813  
                    Mean   :66551  
                    3rd Qu.:74030  
                    Max.   :90089  

This data set is from Current Results. You can find this data here. It provides the average temperature in each state.

summary(State_Temp_and_Rain)

    State           Average Temperature Total Hours of Sunlight   Clear Days    
 Length:50          Min.   :26.60       Min.   :2061            Min.   : 58.00  
 Class :character   1st Qu.:45.25       1st Qu.:2514            1st Qu.: 89.25  
 Mode  :character   Median :51.20       Median :2690            Median :100.50  
                    Mean   :51.94       Mean   :2721            Mean   :103.26  
                    3rd Qu.:58.65       3rd Qu.:2924            3rd Qu.:115.00  
                    Max.   :70.70       Max.   :3806            Max.   :193.00  
                                        NA's   :3                               

This data set is from Researcher Tools. You can find this data here. It provides useful connections between state names, state codes, and regions.

summary(states_with_regions)

    State            State Code           Region           Sub-Region       
 Length:50          Length:50          Length:50          Length:50         
 Class :character   Class :character   Class :character   Class :character  
 Mode  :character   Mode  :character   Mode  :character   Mode  :character  

The Tableau Visualizations

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Map of the United States color-coded by region. This is an interactive map that allows you to filter what is shown on sheet Library Programs vs. Visits and Program Breakdown by Type.

Dual combination showing the number of library programs per 10,000 people and the annual visits per capita for each state. Two calculated measured were created for this visualization.

1. Library_programs_per_10K = [Library_Programs] *10000 / [State_Population]
2. Library_visits_per_capita = [Library_Visits] / [State_Population]

Additionally, a set was created to show High Visit States which is a grouping of states who average more than 5.5 visits per person per year.

The South region has zero states in the High Visit States set. The other three regions have either 4 or 5 states each. This implies that libraries in the south could benefit from talking to the other regions about the kinds of programs they are implementing to get people to go to the library. Additionally, the states in the southern region have noticeably fewer library programs per 10,000 residents. Looking at all of the regions, there is a general positive correlation between the number of programs per 10,000 people and the average number of visits per person. Therefore, if a state wanted to increase the number of visits to public libraries a larger budget could be allocated for library programs.

A stacked bar graph showing the percentage breakdown of total library programs into those for children, adolescents, and those for adults. To determine this, three measure calculations were used, however, these were not stored as new measures. These calculations changed the data from number of programs to a percentage of total programs for each of the three program categories.

1. Calculation for percent children programs: [Childrens_programs] / [Library_programs]
2. Calculation for percent adolescent programs: [Young_adult_programs] / [Library_programs]
3. Calculation for percent adult programs: [Adult_programs] / [Library_programs]

In general, if less than 58% of states library programs are aimed at children then the annual number of visits per capita is lower. Additionally, southern states (on average) offer a lower percentage of children programs than the other three regions. This could be a contributing factor to the lower number of visits to libraries in the south.

This is a dashboard for the previous three visualizations.

Box and whisker plot showing the total digital collection cost, print collection cost, other collection cost, and total collection cost for each state. The visualization has four pages, one for each region.

All four regions spend the most on print collections with digital and other (such as audio) collection costs being roughly similar. Heavily populated states (Texas, California, New York, Ohio) fall outside the interquartile range for collection costs due to the significantly increased volume of collection material required in these larger states.

Scatterplot showing the relationship between the total collection cost and size for each state color-coded by region with a trendline for each region.

From the regional trend lines on this visualization, it can be seen that Midwest and Northeast spend less per collection item than South and West regions. The South and West regions should consult with the material procurement teams in the Midwest and Northeast regions to determine how to reduce collection costs.

This is a dashboard for the previous two visualizations.

A scatter plot showing how the average annual temperature in a state is related to the average annual visits per capita. The average annual visits per capita was found using the following formula: [Library_Visits]/[State_Population]. The points are color-coded by region and have a trend line with a 95% confidence bands.

There is a general trend that the higher the average temperature in a state the fewer number of visits per capita to the libraries. This is a logical, yet interesting result, as warmer temperatures lend themselves more towards being active and outdoors than attending the library.

A crosstab of operational revenue to cost ratio. A red-green scale was used to color the average ratio value of Profit to Expense Ratio with a ratio of 1.0 selected as the transition point between the colors. The crosstab is created with values given by state and separated by sub-region.

Profit to Expense Ratio = [Total_Operating_Revenue]/[Total_Operating_Expenditures]

New England has the lowest revenue to cost ratio. Most of the region’s libraries are profiting but no library is particularly profitable.

A filled map of the United States showing the average number of computers per library for each state. A KPI was created for this statistic and the filled color of each individual state is coordinated to whether or not the KPI is low, medium, or high and the range for each category of the KPI can be adjusted by the user. KPI Low was set to 12 and KPI Medium is set to 19.

KPI Computers per Library =

IF AVG([Public_Internet_Computers] / ([Central_Libraries] + [Branch_Libraries])) <= [KPI Low] THEN “Low” ELSEIF AVG([Public_Internet_Computers] / ([Central_Libraries] + [Branch_Libraries])) <= [KPI Medium] THEN “Medium” ELSE “High” END

KPI Low: ranges from 1 to 12 KPI Medium: ranges from 13 to 20

The midwest has the least computers per library compared to other regions. The South has the most computers per library.

A histogram of showing the annual computer usage and the states that fall into each bin with the bin size being 2.5 million. The columns are labelled with each state fall into the bin. Annual computer usage is measured in number of sessions logged.The KPI Computers per Library was used again in this case. KPI Low was set to 12 and KPI Medium is set to 19.

States that have medium to high amounts of amounts of computers per libraries (blue and red blocks) also tend to have higher amounts of computer usage. This could indicate that the extra computers available to the public allow for more computer usage.

This is a dashboard for the previous two visualizations.

The Shiny Visualizations

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This boxplot shows the minimum, maximum, first quartile, third quartile, and median of the “Cost” values for each expenditure, including Digital Collection Expenditures, Print Collection Expenditures, Other Expenditures, and Total Expenditures. The user may select the “Cost Range” that they would like to see.

This is interesting because you can see how many states are outliers in spending on Digital and Print Expenditures.

This histogram shows the number of Librarians in each state.

This is interesting because you can see the overall trend of lot of states having relatively little Librarians (>300), while one state, New York, has almost a thousand more librarians than the second highest state, CA, created a gap in the histogram.

This graph shows how different states compare in terms of Library Visits per Median Family Income. This uses a join with the 2015 Census data.

This is interesting because it shows a trend that richer states have more library visits. We were surprised by this because libraries provide many services for free that would benefit low income families.

This graph shows the Cost per Category per State. The graph is the colored according to the table calculation: sum(Library_Visits) /sum(Service_Population_Without_Duplicates. The limits for the KPI can be selected by the user.

This is interesting because you can see that Texas has some of the highest library costs in the country, but still has a relatively low number of visitors per service population.

This graph shows the number of Librarians per State, and the fill of the graph is colored according to the table calculation of the number of citizens per Librarian.

This is interesting because you can see that GA has a relatively low number of overall librarians, but has by far the highest ratio of librarians per citizen.

This graph shows compares the total open library hours and the high school enrollment in each state.

This is interesting because, generally speaking, the states with the highest hours open have the highest high school enrollment.